Consecutive seeding and transfer of genetic diversity in metastasis

Modeling tumors as species-rich ecological communities

Many advanced cancers resist therapeutic intervention. This process is fundamentally related to intra-tumor heterogeneity: multiple cell populations, each with different mutational and phenotypic signatures, coexist within a tumor and its metastatic nodes. Like species in an ecosystem, many cancer cell populations are intertwined in a complex network of ecological interactions. Most mathematical models of tumor ecology, however, cannot account for such phenotypic diversity nor are able to predict its consequences. Here we propose that the Generalized Lotka-Volterra model (GLV), a standard tool to describe complex, species-rich ecological communities, provides a suitable framework to describe the ecology of heterogeneous tumors. We develop a GLV model of tumor growth and discuss how its emerging properties, such as outgrowth and multistability, provide a new understanding of the disease. Additionally, we discuss potential extensions of the model and their application to three active areas of cancer research, namely phenotypic plasticity, the cancer-immune interplay and the resistance of metastatic tumors to treatment. Our work outlines a set of questions and a tentative road map for further research in cancer ecology.

Onco-Breastomics: An Eco-Evo-Devo Holistic Approach

Known as a diverse collection of neoplastic diseases, breast cancer (BC) can be hyperbolically characterized as a dynamic pseudo-organ, a living organism able to build a complex, open, hierarchically organized, self-sustainable, and self-renewable tumor system, a population, a species, a local community, a biocenosis, or an evolving dynamical ecosystem (i.e., immune or metabolic ecosystem) that emphasizes both developmental continuity and spatio-temporal change. Moreover, a cancer cell community, also known as an oncobiota, has been described as non-sexually reproducing species, as well as a migratory or invasive species that expresses intelligent behavior, or an endangered or parasite species that fights to survive, to optimize its features inside the host's ecosystem, or that is able to exploit or to disrupt its host circadian cycle for improving the own proliferation and spreading. BC tumorigenesis has also been compared with the early embryo and placenta development that may suggest new strategies for research and therapy. Furthermore, BC has also been characterized as an environmental disease or as an ecological disorder. Many mechanisms of cancer progression have been explained by principles of ecology, developmental biology, and evolutionary paradigms. Many authors have discussed ecological, developmental, and evolutionary strategies for more successful anti-cancer therapies, or for understanding the ecological, developmental, and evolutionary bases of BC exploitable vulnerabilities. Herein, we used the integrated framework of three well known ecological theories: the Bronfenbrenner's theory of human development, the Vannote's River Continuum Concept (RCC), and the Ecological Evolutionary Developmental Biology (Eco-Evo-Devo) theory, to explain and understand several eco-evo-devo-based principles that govern BC progression. Multi-omics fields, taken together as onco-breastomics, offer better opportunities to integrate, analyze, and interpret large amounts of complex heterogeneous data, such as various and big-omics data obtained by multiple investigative modalities, for understanding the eco-evo-devo-based principles that drive BC progression and treatment. These integrative eco-evo-devo theories can help clinicians better diagnose and treat BC, for example, by using non-invasive biomarkers in liquid-biopsies that have emerged from integrated omics-based data that accurately reflect the biomolecular landscape of the primary tumor in order to avoid mutilating preventive surgery, like bilateral mastectomy. From the perspective of preventive, personalized, and participatory medicine, these hypotheses may help patients to think about this disease as a process governed by natural rules, to understand the possible causes of the disease, and to gain control on their own health.

Evolutionary mode and timing of dissemination of high-grade serous carcinomas

Dissemination within the peritoneal cavity is a main determinant of poor patient outcomes from high-grade serous carcinomas (HGSCs). The dissemination process is poorly understood from a cancer evolutionary perspective. We reconstructed the evolutionary trajectories across a median of 5 tumor sites and regions from each of 23 patients based on deep whole-exome sequencing. Polyclonal cancer origin was detected in 1 patient. Ovarian tumors had more complex subclonal architectures than other intraperitoneal tumors in each patient, which indicated that tumors developed earlier in the ovaries. Three common modes of dissemination were identified, including monoclonal or polyclonal dissemination of monophyletic (linear) or polyphyletic (branched) subclones. Mutation profiles of initial or disseminated clones varied greatly among cancers, but recurrent mutations were found in 7 cancer-critical genes, including TP53, BRCA1, BRCA2, and DNMT3A, and in the PI3K/AKT1 pathway. Disseminated clones developed late in the evolutionary trajectory models of most cancers, in particular in cancers with DNA damage repair deficiency. Polyclonal dissemination was predicted to occur predominantly as a single and rapid wave, but chemotherapy exposure was associated with higher genomic diversity of disseminated clones. In conclusion, we described three common evolutionary dissemination modes across HGSCs and proposed factors associated with dissemination diversity.

Intermetastatic and Intrametastatic Heterogeneity Shapes Adaptive Therapy Cycling Dynamics

Adaptive therapies that alternate between drug applications and drug-free vacations can exploit competition between sensitive and resistant cells to maximize the time to progression. However, optimal dosing schedules depend on the properties of metastases, which are often not directly measurable in clinical practice. Here, we proposed a framework for estimating features of metastases through tumor response dynamics during the first adaptive therapy treatment cycle. Longitudinal prostate-specific antigen (PSA) levels in 16 patients with metastatic castration-resistant prostate cancer undergoing adaptive androgen deprivation treatment were analyzed to investigate relationships between cycle dynamics and clinical variables such as Gleason score, the change in the number of metastases over a cycle, and the total number of cycles over the course of treatment. The first cycle of adaptive therapy, which consists of a response period (applying therapy until 50% PSA reduction), and a regrowth period (removing treatment until reaching initial PSA levels), delineated several features of the computational metastatic system: larger metastases had longer cycles; a higher proportion of drug-resistant cells slowed the cycles; and a faster cell turnover rate sped up drug response time and slowed regrowth time. The number of metastases did not affect cycle times, as response dynamics were dominated by the largest tumors rather than the aggregate. In addition, systems with higher intermetastasis heterogeneity responded better to continuous therapy and correlated with dynamics from patients with high or low Gleason scores. Conversely, systems with higher intrametastasis heterogeneity responded better to adaptive therapy and correlated with dynamics from patients with intermediate Gleason scores.

SIGNIFICANCE

Multiscale mathematical modeling combined with biomarker dynamics during adaptive therapy helps identify underlying features of metastatic cancer to inform treatment decisions.

Insights into the metastatic cascade through research autopsies

Metastasis is a complex process and the leading cause of cancer-related death globally. Recent studies have demonstrated that genomic sequencing data from paired primary and metastatic tumours can be used to trace the evolutionary origins of cells responsible for metastasis. This approach has yielded new insights into the genomic alterations that engender metastatic potential, and the mechanisms by which cancer spreads. Given that the reliability of these approaches is contingent upon how representative the samples are of primary and metastatic tumour heterogeneity, we review insights from studies that have reconstructed the evolution of metastasis within the context of their cohorts and designs. We discuss the role of research autopsies in achieving the comprehensive sampling necessary to advance the current understanding of metastasis.

Integrative multi-omics and drug-response characterization of patient-derived prostate cancer primary cells

Prostate cancer (PCa) is the second most prevalent malignancy in males across the world. A greater knowledge of the relationship between protein abundance and drug responses would benefit precision treatment for PCa. Herein, we establish 35 Chinese PCa primary cell models to capture specific characteristics among PCa patients, including gene mutations, mRNA/protein/surface protein distributions, and pharmaceutical responses. The multi-omics analyses identify Anterior Gradient 2 (AGR2) as a pre-operative prognostic biomarker in PCa. Through the drug library screening, we describe crizotinib as a selective compound for malignant PCa primary cells. We further perform the pharmacoproteome analysis and identify 14,372 significant protein-drug correlations. Surprisingly, the diminished AGR2 enhances the inhibition activity of crizotinib via ALK/c-MET-AKT axis activation which is validated by PC3 and xenograft model. Our integrated multi-omics approach yields a comprehensive understanding of PCa biomarkers and pharmacological responses, allowing for more precise diagnosis and therapies.

Agent-based methods facilitate integrative science in cancer

In this opinion, we highlight agent-based modeling as a key tool for exploration of cell-cell and cell-environment interactions that drive cancer progression, therapeutic resistance, and metastasis. These biological phenomena are particularly suited to be captured at the cell-scale resolution possible only within agent-based or individual-based mathematical models. These modeling approaches complement experimental work (in vitro and in vivo systems) through parameterization and data extrapolation but also feed forward to drive new experiments that test model-generated predictions.

Orchestration of Collective Migration and Metastasis by Tumor Cell Clusters

Metastatic dissemination has lethal consequences for cancer patients. Accruing evidence supports the hypothesis that tumor cells can migrate and metastasize as clusters of cells while maintaining contacts with one another. Collective metastasis enables tumor cells to colonize secondary sites more efficiently, resist cell death, and evade the immune system. On the other hand, tumor cell clusters face unique challenges for dissemination particularly during systemic dissemination. Here, we review recent progress toward understanding how tumor cell clusters overcome these disadvantages as well as mechanisms they utilize to gain advantages throughout the metastatic process. We consider useful models for studying collective metastasis and reflect on how the study of collective metastasis suggests new opportunities for eradicating and preventing metastatic disease.

Immunogenomic intertumor heterogeneity across primary and metastatic sites in a patient with lung adenocarcinoma

Background

Lung cancer is the leading cause of cancer death, partially owing to its extensive heterogeneity. The analysis of intertumor heterogeneity has been limited by an inability to concurrently obtain tissue from synchronous metastases unaltered by multiple prior lines of therapy.

Methods

In order to study the relationship between genomic, epigenomic and T cell repertoire heterogeneity in a rare autopsy case from a 32-year-old female never-smoker with left lung primary late-stage lung adenocarcinoma (LUAD), we did whole-exome sequencing (WES), DNA methylation and T cell receptor (TCR) sequencing to characterize the immunogenomic landscape of one primary and 19 synchronous metastatic tumors.

Results

We observed heterogeneous mutation, methylation, and T cell patterns across distinct metastases. Only TP53 mutation was detected in all tumors suggesting an early event while other cancer gene mutations were later events which may have followed subclonal diversification. A set of prevalent T cell clonotypes were completely excluded from left-side thoracic tumors indicating distinct T cell repertoire profiles between left-side and non left-side thoracic tumors. Though a limited number of predicted neoantigens were shared, these were associated with homology of the T cell repertoire across metastases. Lastly, ratio of methylated neoantigen coding mutations was negatively associated with T-cell density, richness and clonality, suggesting neoantigen methylation may partially drive immunosuppression.

Conclusions

Our study demonstrates heterogeneous genomic and T cell profiles across synchronous metastases and how restriction of unique T cell clonotypes within an individual may differentially shape the genomic and epigenomic landscapes of synchronous lung metastases.

Cancer metastasis is related to normal tissue stemness

The occurrence of cancer metastasis may be related to stem cells in normal tissues. We searched for patient IDs with both normal tissue stem cell values and TCGA (The Cancer Genome Atlas) clinical data for pairing and obtained 639 sets of data (stemness index of normal tissue, stemness index of tumor tissue, cancer stage, distant metastasis, tumor size) and invasion, and lymph node involvement). However, clinical data on cancer metastasis are of only four stages (e.g., Stage I, II, III, and IV), which cannot show subtle changes continuously. We need to find an effective data mining method to transform this four-valued clinical description into a numerical curve. We data-mine this data through numericalization, sorting, and noise reduction filtering. The results showed that: as the normal tissue stemness value (NS) increased, the tumor tissue stemness value (TS) increased proportionally (1.26 times NS). When NS >0.5, the rate of change in TS decelerated (0.43 times NS), and tumor metastasis began to occur. Clinical indicators, such as cancer stage, distant metastasis, tumor size and invasion, and lymph node involvement, showed that tumor metastasis became more and more severe with the increase of NS. This study suggests that tumor metastasis is triggered when the NS in the patient's body is more significant than 0.5.

Inferring parameters of cancer evolution in chronic lymphocytic leukemia

As a cancer develops, its cells accrue new mutations, resulting in a heterogeneous, complex genomic profile. We make use of this heterogeneity to derive simple, analytic estimates of parameters driving carcinogenesis and reconstruct the timeline of selective events following initiation of an individual cancer, where two longitudinal samples are available for sequencing. Using stochastic computer simulations of cancer growth, we show that we can accurately estimate mutation rate, time before and after a driver event occurred, and growth rates of both initiated cancer cells and subsequently appearing subclones. We demonstrate that in order to obtain accurate estimates of mutation rate and timing of events, observed mutation counts should be corrected to account for clonal mutations that occurred after the founding of the tumor, as well as sequencing coverage. Chronic lymphocytic leukemia (CLL), which often does not require treatment for years after diagnosis, presents an optimal system to study the untreated, natural evolution of cancer cell populations. When we apply our methodology to reconstruct the individual evolutionary histories of CLL patients, we find that the parental leukemic clone typically appears within the first fifteen years of life.

Genetic Clonality as the Hallmark Driving Evolution of Non-Small Cell Lung Cancer

Simple Summary

Limited knowledge about NSCLC evolution has affected therapeutic strategies for many decades. The application of NGS-based techniques to studies on ITH has provided genetic insight into the contribution of clonality primary seeding, as well as to distant dissemination. To date, multiregional ITH affects accurate diagnosis and treatment decisions and is considered the main hallmark of anticancer therapy failure. Understanding the evolutionary trajectories that drive the metastatic process is critical for improving treatment strategies for this deadly condition. In this review, we discuss how the clonality of genetic alterations influence the seeding of primary and metastatic lesions of NSCLC, highlighting that wide genetic analyses may reveal the phylogenetic lineages of NSCLC evolution.

Abstract

Data indicate that many driver alterations from the primary tumor of non-small cell lung cancer (NSCLC) are predominantly shared across all metastases; however, disseminating cells may also acquire a new genetic landscape across their journey. By comparing the constituent subclonal mutations between pairs of primary and metastatic samples, it is possible to derive the ancestral relationships between tumor clones, rather than between tumor samples. Current treatment strategies mostly rely on the theory that metastases are genetically similar to the primary lesions from which they arise. However, intratumor heterogeneity (ITH) affects accurate diagnosis and treatment decisions and it is considered the main hallmark of anticancer therapy failure. Understanding the genetic changes that drive the metastatic process is critical for improving the treatment strategies of this deadly condition. Application of next generation sequencing (NGS) techniques has already created knowledge about tumorigenesis and cancer evolution; however, further NGS implementation may also allow to reconstruct phylogenetic clonal lineages and clonal expansion. In this review, we discuss how the clonality of genetic alterations influence the seeding of primary and metastatic lesions of NSCLC. We highlight that wide genetic analyses may reveal the phylogenetic trajectories of NSCLC evolution, and may pave the way to better management of follow-up and treatment.

Single-cell transcriptomics links malignant T cells to the tumor immune landscape in cutaneous T cell lymphoma

Cutaneous T cell lymphoma (CTCL) represents a heterogeneous group of non-Hodgkin lymphoma distinguished by the presence of clonal malignant T cells. The heterogeneity of malignant T cells and the complex tumor microenvironment remain poorly characterized. With single-cell RNA analysis and bulk whole-exome sequencing on 19 skin lesions from 15 CTCL patients, we decipher the intra-tumor and inter-lesion diversity of CTCL patients and propose a multi-step tumor evolution model. We further establish a subtyping scheme based on the molecular features of malignant T cells and their pro-tumorigenic microenvironments: the T_CyEM group, demonstrating a cytotoxic effector memory T cell phenotype, shows more M2 macrophages infiltration, while the T_CM group, featured by a central memory T cell phenotype and adverse patient outcome, is infiltrated by highly exhausted CD8⁺ reactive T cells, B cells and Tregs with suppressive activities. Our results establish a solid basis for understanding the nature of CTCL and pave the way for future precision medicine for CTCL patients.

Multiparametric Circulating Tumor Cell Analysis to Select Targeted Therapies for Breast Cancer Patients

Simple Summary

Liquid biopsies may act as a dynamic tool for identification of targets for precision therapy while circumventing limitations of tissue biopsies. In opposite to most liquid biopsy-related studies that analyze limited patient material for only one parameter, this study is based on a longitudinal and multiparametric analysis of circulating tumor cells (CTCs). A metastatic breast cancer patient was followed over a period of three years and analyses of the genome, RNA profiling, and in vitro drug testing on cultured CTCs were performed in a unique manner. We show that combining the strengths of multiple technologies for analysis yielded maximum information on the ongoing disease and, eventually, allowed choosing an effective therapy, which led to a massive reduction in CTC numbers. This approach provides a concept for future detailed longitudinal and multiparametric CTC analyses.

Abstract

Background: The analysis of liquid biopsies, e.g., circulating tumor cells (CTCs) is an appealing diagnostic concept for targeted therapy selection. In this proof-of-concept study, we aimed to perform multiparametric analyses of CTCs to select targeted therapies for metastatic breast cancer patients. Methods: First, CTCs of five metastatic breast cancer patients were analyzed by whole exome sequencing (WES). Based on the results, one patient was selected and monitored by longitudinal and multiparametric liquid biopsy analyses over more than three years, including WES, RNA profiling, and in vitro drug testing of CTCs. Results: Mutations addressable by targeted therapies were detected in all patients, including mutations that were not detected in biopsies of the primary tumor. For the index patient, the clonal evolution of the tumor cells was retraced and resistance mechanisms were identified. The AKT1 E17K mutation was uncovered as the driver of the metastatic process. Drug testing on the patient’s CTCs confirmed the efficacy of drugs targeting the AKT1 pathway. During a targeted therapy chosen based on the CTC characterization and including the mTOR inhibitor everolimus, CTC numbers dropped by 97.3% and the disease remained stable as determined by computer tomography/magnetic resonance imaging. Conclusion: These results illustrate the strength of a multiparametric CTC analysis to choose and validate targeted therapies to optimize cancer treatment in the future. Furthermore, from a scientific point of view, such studies promote the understanding of the biology of CTCs during different treatment regimens.

Combined multimodal ctDNA analysis and radiological imaging for tumor surveillance in Non-small cell lung cancer

BACKGROUND

Radiology is the current standard for monitoring treatment responses in lung cancer. Limited sensitivity, exposure to ionizing radiations and related sequelae constitute some of its major limitation. Non-invasive and highly sensitive methods for early detection of treatment failures and resistance-associated disease progression would have additional clinical utility.

METHODS

We analyzed serially collected plasma and paired tumor samples from lung cancer patients (61 with stage IV, 48 with stages I-III disease) and 61 healthy samples by means of next-generation sequencing, radiological imaging and droplet digital polymerase chain reaction (ddPCR) mutation and methylation assays.

RESULTS

A 62% variant concordance between tumor-reported and circulating-free DNA (cfDNA) sequencing was observed between baseline liquid and tissue biopsies in stage IV patients. Interestingly, ctDNA sequencing allowed for the identification of resistance-mediating p.T790M mutations in baseline plasma samples for which no such mutation was observed in the corresponding tissue. Serial circulating tumor DNA (ctDNA) mutation analysis by means of ddPCR revealed a general decrease in ctDNA loads between baseline and first reassessment. Additionally, serial ctDNA analyses only recapitulated computed tomography (CT) -monitored tumor dynamics of some, but not all lesions within the same patient. To complement ctDNA variant analysis we devised a ctDNA methylation assay (^methcfDNA) based on methylation-sensitive restriction enzymes. cfDNA methylation showed and area under the curve (AUC) of > 0.90 in early and late stage cases. A decrease in ^methcfDNA between baseline and first reassessment was reflected by a decrease in CT-derive tumor surface area, irrespective of tumor mutational status.

CONCLUSION

Taken together, our data support the use of cfDNA sequencing for unbiased characterization of the molecular tumor architecture, highlights the impact of tumor architectural heterogeneity on ctDNA-based tumor surveillance and the added value of complementary approaches such as cfDNA methylation for early detection and monitoring.

Models of pancreatic ductal adenocarcinoma

Although pancreatic cancer remains to be a leading cause of cancer-related deaths in many industrialized countries, there have been major advances in research over the past two decades that provided a detailed insight into the molecular and developmental processes that govern the genesis of this highly malignant tumor type. There is a continuous need for the development and analysis of preclinical and genetically engineered pancreatic cancer models to study the biological significance of new molecular targets that are identified using various genome-wide approaches and to better understand the mechanisms by which they contribute to pancreatic cancer onset and progression. Following an introduction into the etiology of pancreatic cancer, the molecular subtypes, and key signaling pathways, this review provides an overview of the broad spectrum of models for pancreatic cancer research. In addition to conventional and patient-derived xenografting, this review highlights major milestones in the development of chemical carcinogen-induced and genetically engineered animal models to study pancreatic cancer. Particular emphasis was placed on selected research findings of ligand-controlled tumor models and current efforts to develop genetically engineered strains to gain insight into the biological functions of genes at defined developmental stages during cancer initiation and metastatic progression.

Selection of metastasis competent subclones in the tumour interior

The genetic evolutionary features of solid tumour growth are becoming increasingly well described, but the spatial and physical nature of subclonal growth remains unclear. Here, we utilize 102 macroscopic whole-tumour images from clear cell renal cell carcinoma patients, with matched genetic and phenotypic data from 756 biopsies. Utilizing a digital image processing pipeline, a renal pathologist marked the boundaries between tumour and normal tissue and extracted positions of boundary line and biopsy regions to X and Y coordinates. We then integrated coordinates with genomic data to map exact spatial subclone locations, revealing how genetically distinct subclones grow and evolve spatially. We observed a phenotype of advanced and more aggressive subclonal growth in the tumour centre, characterized by an elevated burden of somatic copy number alterations and higher necrosis, proliferation rate and Fuhrman grade. Moreover, we found that metastasizing subclones preferentially originate from the tumour centre. Collectively, these observations suggest a model of accelerated evolution in the tumour interior, with harsh hypoxic environmental conditions leading to a greater opportunity for driver somatic copy number alterations to arise and expand due to selective advantage. Tumour subclone growth is predominantly spatially contiguous in nature. We found only two cases of subclone dispersal, one of which was associated with metastasis. The largest subclones spatially were dominated by driver somatic copy number alterations, suggesting that a large selective advantage can be conferred to subclones upon acquisition of these alterations. In conclusion, spatial dynamics is strongly associated with genomic alterations and plays an important role in tumour evolution.

Elements and evolutionary determinants of genomic divergence between paired primary and metastatic tumors

Can metastatic-primary (M-P) genomic divergence measured from next generation sequencing reveal the natural history of metastatic dissemination? This remains an open question of utmost importance in facilitating a deeper understanding of metastatic progression, and thereby, improving its prevention. Here, we utilize mathematical and computational modeling to tackle this question as well as to provide a framework that illuminates the fundamental elements and evolutionary determinants of M-P divergence. Our framework facilitates the integration of sequencing detectability of somatic variants, and hence, paves the way towards bridging the measurable between-tumor heterogeneity with analytical modeling and interpretability. We show that the number of somatic variants of the metastatic seeding cell that are experimentally undetectable in the primary tumor, can be characterized as the path of the phylogenetic tree from the last appearing variant of the seeding cell back to the most recent detectable variant. We find that the expected length of this path is principally determined by the decay in detectability of the variants along the seeding cell's lineage; and thus, exhibits a significant dependence on the underlying tumor growth dynamics. A striking implication of this fact, is that dissemination from an advanced detectable subclone of the primary tumor can lead to an abrupt drop in the expected measurable M-P divergence, thereby breaking the previously assumed monotonic relation between seeding time and M-P divergence. This is emphatically verified by our single cell-based spatial tumor growth simulation, where we find that M-P divergence exhibits a non-monotonic relationship with seeding time when the primary tumor grows under branched and linear evolution. On the other hand, a monotonic relationship holds when we condition on the dynamics of progressive diversification, or by restricting the seeding cells to always originate from undetectable subclones. Our results highlight the fact that a precise understanding of tumor growth dynamics is the sine qua non for exploiting M-P divergence to reconstruct the chronology of metastatic dissemination. The quantitative models presented here enable further careful evaluation of M-P divergence in association with crucial evolutionary and sequencing parameters.

Single-cell lineages reveal the rates, routes, and drivers of metastasis in cancer xenografts

Detailed phylogenies of tumor populations can recount the history and chronology of critical events during cancer progression, such as metastatic dissemination. We applied a Cas9-based, single-cell lineage tracer to study the rates, routes, and drivers of metastasis in a lung cancer xenograft mouse model. We report deeply resolved phylogenies for tens of thousands of cancer cells traced over months of growth and dissemination. This revealed stark heterogeneity in metastatic capacity, arising from preexisting and heritable differences in gene expression. We demonstrate that these identified genes can drive invasiveness and uncovered an unanticipated suppressive role for KRT17 We also show that metastases disseminated via multidirectional tissue routes and complex seeding topologies. Overall, we demonstrate the power of tracing cancer progression at subclonal resolution and vast scale.

Malignant subclone drives metastasis of genetically and phenotypically heterogenous cell clusters through fibrotic niche generation

A concept of polyclonal metastasis has recently been proposed, wherein tumor cell clusters break off from the primary site and are disseminated. However, the involvement of driver mutations in such polyclonal mechanism is not fully understood. Here, we show that non-metastatic AP cells metastasize to the liver with metastatic AKTP cells after co-transplantation to the spleen. Furthermore, AKTP cell depletion after the development of metastases results in the continuous proliferation of the remaining AP cells, indicating a role of AKTP cells in the early step of polyclonal metastasis. Importantly, AKTP cells, but not AP cells, induce fibrotic niche generation when arrested in the sinusoid, and such fibrotic microenvironment promotes the colonization of AP cells. These results indicate that non-metastatic cells can metastasize via the polyclonal metastasis mechanism using the fibrotic niche induced by malignant cells. Thus, targeting the fibrotic niche is an effective strategy for halting polyclonal metastasis.

Transitional dynamics of cancer stem cells in invasion and metastasis

At the onset, few cancer cells amidst the tumor bulk, identified as cancer stem cells (CSCs) or early disseminated cancer cells (eDCCs) are capable of survival post conventional therapy and persist as minimal residual disease (MRD). Metastatic subclones emerge both early and late in the life of primary tumor ensuing an ongoing regional clonal evolution of progenitor cells in metastatic and primary tumors. In the last decade, multiple studies proposed various identities of stem-like cells that undergo transitions to adapt to the changing microenvironment as the disease progresses. This review advocates with substantial evidence the dynamic model of tumor propagation by exploring the specific cell types, reversible phenotypic plasticity between the tumorigenic leader seeds and the supporting follower cancer cells both in circulation and in solid tissue to accurately decipher tumor promoting clones and its role in metastatic dissemination and tumor re-growth. (142 words).

Cancer progression and the invisible phase of metastatic colonization

Metastatic dissemination occurs very early in the malignant progression of a cancer but the clinical manifestation of metastases often takes years. In recent decades, 5-year survival of patients with many solid cancers has increased due to earlier detection, local disease control and adjuvant therapies. As a consequence, we are confronted with an increase in late relapses as more antiproliferative cancer therapies prolong disease courses, raising questions about how cancer cells survive, evolve or stop growing and finally expand during periods of clinical latency. I argue here that the understanding of early metastasis formation, particularly of the currently invisible phase of metastatic colonization, will be essential for the next stage in adjuvant therapy development that reliably prevents metachronous metastasis.

Physical Activity Reduces the Risk of Recurrence and Mortality in Cancer Patients

The biological mechanisms through which physical activity reduces metastatic disease recurrence and mortality in cancer patients are not known. This review offers the hypothesis that physical activity reduces the risk of recurrence and mortality in cancer patients through two synergistic processes: 1) indirect (systemic) effects related to the host tumor microenvironment; and 2) direct (physical) effects on cancer cells.

Clonal Evolution and Timing of Metastatic Colorectal Cancer

Colorectal cancer (CRC) is the third most frequently diagnosed cancer worldwide, where ~50% of patients develop metastasis, despite current improved management. Genomic characterisation of metastatic CRC, and elucidating the effects of therapy on the metastatic process, are essential to help guide precision medicine. Multi-region whole-exome sequencing was performed on 191 sampled tumour regions of patient-matched therapy-naïve and treated CRC primary tumours (n = 92 tumour regions) and metastases (n = 99 tumour regions), in 30 patients. Somatic variants were analysed to define the origin, composition, and timing of seeding in the metastatic progression of therapy-naïve and treated metastatic CRC. High concordance, with few genomic differences, was observed between primary CRC and metastases. Most cases supported a late dissemination model, via either monoclonal or polyclonal seeding. Polyclonal seeding appeared more common in therapy-naïve metastases than in treated metastases. Whereby, treatment prompted for the selection of distinct resistant clones, through monoclonal seeding to distant metastatic sites. Overall, this study reinforces the importance of early clinical detection and surgical excision of the CRC tumour, whilst further highlighting the clinical challenges for metastatic CRC with increased intratumour heterogeneity (either due to early dissemination or polyclonal metastatic spread) and the underlying risk of future therapeutic resistance in treated patients.

Independent evolution of cutaneous lymphoma subclones in different microenvironments of the skin

Mycosis fungoides (MF) is the most common cutaneous T-cell lymphoma. Lesions of MF are formed by hematogenous seeding the skin with polyclonal (clonotypically diverse) neoplastic T-cells which accumulate numerous mutations and display a high degree of mutational, intratumoral heterogeneity (ITH). A characteristic but poorly studied feature of MF is epidermotropism, the tendency to infiltrate skin epithelial layer (epidermis) in addition to the vascularized dermis. By sequencing the exomes of the microdissected clusters of lymphoma cells from the epidermis and the dermis, we found that those microenvironments comprised different malignant clonotypes. Subclonal structure witnessed the independent mutational evolution in the epidermis and dermis. Thus, the epidermal involvement in MF could not be explained by gradual infiltration from the dermis but was caused by a separate seeding process followed by a quasi-neutral, branched evolution. In conclusion, tissue microenvironments shape the subclonal architecture in MF leading to “ecological heterogeneity” which contributes to the total ITH. Since ITH adversely affects cancer prognosis, targeting the microenvironment may present therapeutic opportunities in MF and other cancers.

Circulating tumor cells as Trojan Horse for understanding, preventing, and treating cancer: a critical appraisal

Circulating tumor cells (CTCs) are regarded as harbingers of metastases. Their ability to predict response to therapy, relapse, and resistance to treatment has proposed their value as putative diagnostic and prognostic indicators. CTCs represent one of the zeniths of cancer evolution in terms of cell survival; however, the triggers of CTC generation, the identification of potentially metastatic CTCs, and the mechanisms contributing to their heterogeneity and aggressiveness represent issues not yet fully deciphered. Thus, prior to enabling liquid biopsy applications to reach clinical prime time, understanding how the above mechanistic information can be applied to improve treatment decisions is a key challenge. Here, we provide our perspective on how CTCs can provide mechanistic insights into tumor pathogenesis, as well as on CTC clinical value. In doing so, we aim to (a) describe how CTCs disseminate from the primary tumor, and their link to epithelial-mesenchymal transition (EMT); (b) trace the route of CTCs through the circulation, focusing on tumor self-seeding and the possibility of tertiary metastasis; (c) describe possible mechanisms underlying the enhanced metastatic potential of CTCs; (d) discuss how CTC could provide further information on the tissue of origin, especially in cancer of unknown primary origin. We also provide a comprehensive review of meta-analyses assessing the prognostic significance of CTCs, to highlight the emerging role of CTCs in clinical oncology. We also explore how cell-free circulating tumor DNA (ctDNA) analysis, using a combination of genomic and phylogenetic analysis, can offer insights into CTC biology, including our understanding of CTC heterogeneity and tumor evolution. Last, we discuss emerging technologies, such as high-throughput quantitative imaging, radiogenomics, machine learning approaches, and the emerging breath biopsy. These technologies could compliment CTC and ctDNA analyses, and they collectively represent major future steps in cancer detection, monitoring, and management.

The Lymphatic Vasculature in the 21st Century: Novel Functional Roles in Homeostasis and Disease

Mammals have two specialized vascular circulatory systems: the blood vasculature and the lymphatic vasculature. The lymphatic vasculature is a unidirectional conduit that returns filtered interstitial arterial fluid and tissue metabolites to the blood circulation. It also plays major roles in immune cell trafficking and lipid absorption. As we discuss in this review, the molecular characterization of lymphatic vascular development and our understanding of this vasculature's role in pathophysiological conditions has greatly improved in recent years, changing conventional views about the roles of the lymphatic vasculature in health and disease. Morphological or functional defects in the lymphatic vasculature have now been uncovered in several pathological conditions. We propose that subtle asymptomatic alterations in lymphatic vascular function could underlie the variability seen in the body's response to a wide range of human diseases.

Lymph node metastases develop through a wider evolutionary bottleneck than distant metastases

Genetic diversity among metastases is poorly understood but contains important information about disease evolution at secondary sites. Here we investigate inter- and intra-lesion heterogeneity for two types of metastases that associate with different clinical outcomes: lymph node and distant organ metastases in human colorectal cancer. We develop a rigorous mathematical framework for quantifying metastatic phylogenetic diversity. Distant metastases are typically monophyletic and genetically similar to each other. Lymph node metastases, in contrast, display high levels of inter-lesion diversity. We validate these findings by analyzing 317 multi-region biopsies from an independent cohort of 20 patients. We further demonstrate higher levels of intra-lesion heterogeneity in lymph node than in distant metastases. Our results show that fewer primary tumor lineages seed distant metastases than lymph node metastases, indicating that the two sites are subject to different levels of selection. Thus, lymph node and distant metastases develop through fundamentally different evolutionary mechanisms.

Skin colonization by circulating neoplastic clones in cutaneous T-cell lymphoma

Mycosis fungoides (MF) is a mature T-cell lymphoma currently thought to develop primarily in the skin by a clonal expansion of a transformed, resident memory T cell. However, this concept does not explain the key characteristics of MF, such as the debut with multiple, widespread skin lesions or inability of skin-directed therapies to provide cure. The testable inference of the mature T-cell theory is the clonality of MF with respect to all rearranged T-cell receptor (TCR) genes. Here, we used a whole-exome sequencing approach to detect and quantify TCR-α, β, and γ clonotypes in tumor cell clusters microdissected from MF lesions. This method allowed us to calculate the tumor cell fraction of the sample and therefore an unequivocal identification of the TCR clonotypes as neoplastic. Analysis of TCR sequences from 29 patients with MF stage I to IV proved the existence of multiple T-cell clones within the tumor cell fraction, with a considerable variation between patients and between lesions from the same patient (median, 11 clones; range, 2-80 clones/sample). We have also detected multiple neoplastic clones in the peripheral blood in all examined patients. Based on these findings, we propose that circulating neoplastic T-cell clones continuously replenish the lesions of MF, thus increasing their heterogeneity by a mechanism analogous to the consecutive tumor seeding. We hypothesize that circulating neoplastic clones might be a promising target for therapy and could be exploited as a potential biomarker in MF.

Tumour mutational burden: primary versus metastatic tissue creates systematic bias

Tumour mutational burden (TMB) has emerged as a reproducible biomarker to predict immunotherapy response across multiple cancer types. However, a key aspect of TMB measurement that is often overlooked is the source of tissue sample used, which creates a potential for systematic bias. The predominant source is either primary or metastatic tumour tissue. Primary tumours are more heterogeneous and reflect a longer period of tumour evolution, whereas metastases tend to have a more monoclonal structure and potentially different TMB scores. Studies to date measuring TMB have used a heterogeneous set of primary and metastatic tissues, which may explain some of the variability in predictive TMB values across studies. This paper presents data to show that there is a systematic difference whereby metastatic TMB is biased towards higher values than primary TMB (36% higher, paired Wilcoxon, P = 0.0008). However, effectiveness in predicting overall survival during immune checkpoint inhibitor therapy was found to be equivalent between primary and metastatic TMB. We highlight that lower TMB in primary tissue may be important in cases with borderline primary TMB, where assaying metastatic TMB may lead to a different treatment stratification result. As TMB progresses towards clinical implementation, particularly in classically non-immunogenic tumour types, it is important to have better curated trials with either the source of tissue annotated or a prospective study assessing concordance between paired primary and metastatic tissue.

An analysis of genetic heterogeneity in untreated cancers

Genetic intratumoural heterogeneity is a natural consequence of imperfect DNA replication. Any two randomly selected cells, whether normal or cancerous, are therefore genetically different. Here, we review the different forms of genetic heterogeneity in cancer and re-analyse the extent of genetic heterogeneity within seven types of untreated epithelial cancers, with particular regard to its clinical relevance. We find that the homogeneity of predicted functional mutations in driver genes is the rule rather than the exception. In primary tumours with multiple samples, 97% of driver-gene mutations in 38 patients were homogeneous. Moreover, among metastases from the same primary tumour, 100% of the driver mutations in 17 patients were homogeneous. With a single biopsy of a primary tumour in 14 patients, the likelihood of missing a functional driver-gene mutation that was present in all metastases was 2.6%. Furthermore, all functional driver-gene mutations detected in these 14 primary tumours were present among all their metastases. Finally, we found that individual metastatic lesions responded concordantly to targeted therapies in 91% of 44 patients. These analyses indicate that the cells within the primary tumours that gave rise to metastases are genetically homogeneous with respect to functional driver-gene mutations, and we suggest that future efforts to develop combination therapies have the potential to be curative.